New concepts and techniques are replacing traditional methods of water quality parameters measurement systems. In modern sensor era, Optical Sensors (OS), Microelectronic Mechanical Systems (MEMS) and Bio-Sensors are important sensing techniques for different water quality parameter detection. Furthermore, these sensors are highly selective, sensitive, economical and user-friendly with quick response. This paper comprehensively reviews and discuss role of emerging techniques in detection of important water quality parameters i.e Dissolved Oxygen, Turbidity, pH, E-Coli, Effective chlorination, Biochemical Oxygen Demand (B.O.D) and fluoride. In addition, also explains why modern water quality parameters sensing techniques are preferable option for detection of above mentioned parameters. A dedicated part of this paper also discusses the significant advantages and limitations of new available techniques.

Abstract. New concepts and techniques are replacing traditional methods of water quality parameter measurement systems. This paper introduces a cyber-physical system (CPS) approach for water quality assessment in a distribution network. Cyber-physical systems with embedded sensors, processors and actuators can be designed to sense and interact with the water environment. The proposed CPS is comprised of sensing framework integrated with five different water quality parameter sensor nodes and soft computing framework for computational modelling. Soft computing framework utilizes the applications of Python for user interface and fuzzy sciences for decision making. Introduction of multiple sensors in a water distribution network generates a huge number of data matrices, which are sometimes highly complex, difficult to understand and convoluted for effective decision making. Therefore, the proposed system framework also intends to simplify the complexity of obtained sensor data matrices and to support decision making for water engineers through a soft computing framework. The target of this proposed research is to provide a simple and efficient method to identify and detect presence of contamination in a water distribution network using applications of CPS.

The value of interdisciplinarity for solving complex coastal problems is widely recognized. Many early career researchers (ECRs) therefore actively seek this type of collaboration through choice or necessity, for professional development or project funding. However, establishing and conducting interdisciplinary research collaborations as an ECR has many challenges. Here, we identify these challenges through the lens of ECRs working in different disciplines on a common ecosystem, the Norwegian Skagerrak coast. The most densely populated coastline in Norway, the Skagerrak coast, is experiencing a multitude of anthropogenic stressors including fishing, aquaculture, eutrophication, climate change, land runoff, development, and invasive species. The Skagerrak coastline has also been the focus of environmental science research for decades, much of which aims to inform management of these stressors. The region provides a fantastic opportunity for interdisciplinary collaboration, both within and beyond the environmental sciences. This perspective article identifies the barriers ECRs in Norway face in establishing interdisciplinary and collaborative research to inform management of coastal ecosystems, along with their root causes. We believe our discussion will be of broad interest to all research institutions who employ or educate ECRs (in Norway and worldwide), and to those who develop funding mechanisms for ECRs and interdisciplinary research.

<p><strong>Abstract.</strong> New concepts and techniques are replacing traditional methods of water quality parameters measurement systems. This paper introduces the Cyber Physical System (CPS) approach for water quality assessment in distribution network. The proposed CPS consist of (a.) Sensing framework (b.) Soft Computing framework for computational modelling and data analysis. Sensing frame work consist of integrated Multi Sensor Array (MSA) and Soft Computing framework utilizes the applications of Python for user interface and Fuzzy Sciences for decision making. Extensive research suggest that pH, Dissolved Oxygen (D.O.), Electrical Conductivity (E.C.), Oxygen Reduction Potential (O.R.P.) and Temperature are suitable water quality parameters. Therefore, individual sensor of each parameter has been integrated to form Integrated MSA. Soft Computing mainly consist of Python framework for user interface and fuzzy logic for decision support system. Target of this proposed research is to provide simple, efficient, cost effective and socially acceptable means to detect the presence of contamination in water distribution network using applications of CPS.</p>